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Machine Heart

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Machine Heart
Machine Heart
May 28, 2026 · Artificial Intelligence

UNSL: A Unified Multivariate Scaling Law for Predicting Large Model Performance

The article explains that traditional neural scaling laws consider only parameters, data, and compute, while real training involves many variables, and introduces the Unified Neural Scaling Law (UNSL) from Mila and DeepMind, which incorporates multivariate interactions, bottlenecks, hyperbreaks, overfitting, and hyper‑parameter effects, showing superior extrapolation on vision and language benchmarks.

DeepMindLanguage ModelsMila
0 likes · 9 min read
UNSL: A Unified Multivariate Scaling Law for Predicting Large Model Performance
Machine Heart
Machine Heart
May 28, 2026 · Artificial Intelligence

Can a Pre‑trained Embodied Model Work Out‑of‑the‑Box? New Chinese Open‑Source VLA Model Shows Yes

The newly open‑sourced Wall‑OSS‑0.5 VLA model demonstrates that a large‑scale pre‑trained embodied robot brain can achieve strong zero‑shot performance on 17 real‑world tasks, exhibit staircase emergence with longer pre‑training, and far surpass the industry baseline after fine‑tuning, while also revealing current precision limits.

Embodied AIVLAbenchmark
0 likes · 15 min read
Can a Pre‑trained Embodied Model Work Out‑of‑the‑Box? New Chinese Open‑Source VLA Model Shows Yes
Machine Heart
Machine Heart
May 28, 2026 · Industry Insights

Why Jensen Huang Joined Tsinghua University's School of Economics and Management Advisory Board

Jensen Huang, Nvidia's CEO, accepted an invitation to serve on Tsinghua University's School of Economics and Management Advisory Committee—a body that links academia with global business leaders—while U.S. export controls tighten, offering Nvidia a strategic channel to maintain ties with China and expand its AI influence.

China-US Tech CompetitionIndustry Advisory BoardJensen Huang
0 likes · 6 min read
Why Jensen Huang Joined Tsinghua University's School of Economics and Management Advisory Board
Machine Heart
Machine Heart
May 27, 2026 · Artificial Intelligence

RoboMemArena: A Comprehensive Benchmark that Truly Tests Robot Memory for Embodied AI

RoboMemArena introduces a systematic, long‑horizon robot memory benchmark with 26 tasks, 151 sub‑tasks, multimodal annotations, and real‑robot evaluations, exposing the limitations of existing benchmarks and demonstrating that the dual‑system PrediMem model markedly outperforms baselines both in simulation and on physical robots.

Embodied AIPrediMemRoboMemArena
0 likes · 9 min read
RoboMemArena: A Comprehensive Benchmark that Truly Tests Robot Memory for Embodied AI
Machine Heart
Machine Heart
May 27, 2026 · Artificial Intelligence

AMD Paper Finds FP4 Training Instability Is Not Due to Randomness, 9‑10% Speedup

The authors demonstrate that FP4 training instability stems from structural micro‑scaling errors in the weight‑gradient path rather than insufficient randomness, and show that a deterministic Hadamard rotation restores convergence, delivering a 9‑10% end‑to‑end speedup on native FP4 hardware (AMD MI355X) while incurring only 8‑9% token overhead.

Deterministic HadamardFP4MXFP4
0 likes · 10 min read
AMD Paper Finds FP4 Training Instability Is Not Due to Randomness, 9‑10% Speedup
Machine Heart
Machine Heart
May 27, 2026 · Artificial Intelligence

Samsung’s Bold Move from Foundation Models to Physical AI: Leveraging ROM‑Based Architecture and New Benchmarks

Samsung is rapidly building its own foundation model ecosystem, introducing the memory‑based Meki architecture to leverage ROM for edge AI, the multi‑domain M2RL reinforcement‑learning paradigm, and the LiveClawBench 3‑dimensional benchmark to evaluate physical‑world AI, signaling a strategic shift from cloud‑centric to physical AI deployment.

Edge AIFoundation ModelLiveClawBench
0 likes · 8 min read
Samsung’s Bold Move from Foundation Models to Physical AI: Leveraging ROM‑Based Architecture and New Benchmarks
Machine Heart
Machine Heart
May 27, 2026 · Artificial Intelligence

How NeoteAI’s Tactile Embodied AI Lets Robots ‘Feel’ the World – Near‑100 M CNY Angel Round

NeoteAI, a Fudan‑affiliated startup, raised nearly 100 million yuan to advance its visual‑tactile sensor, large‑scale data platform, and VTLA model that together give robots precise touch perception, boosting fine‑grained manipulation success rates above 90% in industrial settings.

AI modelEmbodied AIindustrial automation
0 likes · 10 min read
How NeoteAI’s Tactile Embodied AI Lets Robots ‘Feel’ the World – Near‑100 M CNY Angel Round
Machine Heart
Machine Heart
May 27, 2026 · Artificial Intelligence

CVPR 2026: Learning Camera Pose from 10M Unlabeled Driving Videos

LA‑Pose shows that a model can acquire accurate camera pose estimation for autonomous driving by self‑supervised pretraining on roughly ten million unlabeled driving video clips and fine‑tuning with only a small amount of high‑quality 3D annotations, achieving over 10% accuracy gains while drastically reducing labeling cost.

Autonomous DrivingCVPR 2026LA-Pose
0 likes · 8 min read
CVPR 2026: Learning Camera Pose from 10M Unlabeled Driving Videos